Characterizing diesel fuel spray cone angle from back-scattered imaging by fitting gaussian profiles to radial spray intensity distributions
Document Type
Article
Publication Date
4-24-2012
Abstract
Quantifying fuel spray properties including penetration, cone angle, and vaporization processes sheds light on fuel-air mixing phenomenon, which governs subsequent combustion and emissions formation in diesel engines. Accurate experimental determination of these spray properties is a challenge but imperative to validate computational fluid dynamic (CFD) models for combustion prediction. This study proposes a new threshold independent method for determination of spray cone angle when using Mie back-scattering optical diagnostics to visualize diesel sprays in an optically accessible constant volume vessel. Test conditions include the influence of charge density (17.6 and 34.9 kg/m 3) at 1990 bar injection pressure, and the influence of injection pressure (990, 1370, and 1980 bar) at a charge density of 34.8 kg/m 3 on diesel fuel spray formation from a multi-hole injector into nitrogen at a temperature of 100 C. Conventional thresholding to convert an image to black and white for processing and determination of cone angle is threshold subjective. As an alternative, an image processing method was developed, which fits a Gaussian curve to the intensity distribution of the spray at radial spray cross-sections and uses the resulting parameters to define the spray edge and hence cone angle. This Gaussian curve fitting methodology is shown to provide a robust method for cone angle determination, accounting for reductions in intensity at the radial spray edge. Results are presented for non-vaporizing sprays using this Gaussian curve fitting method and compared to the conventional thresholding based method. © 2012 American Society of Mechanical Engineers.
Publication Title
Journal of Engineering for Gas Turbines and Power
Recommended Citation
Johnson, J.,
Naber, J.,
&
Lee, S.
(2012).
Characterizing diesel fuel spray cone angle from back-scattered imaging by fitting gaussian profiles to radial spray intensity distributions.
Journal of Engineering for Gas Turbines and Power,
134(6).
http://doi.org/10.1115/1.4005994
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/11695